We propose to develop technology for an automated functional analysis of large sets of high-throughput molecular data in the framework of human pathways. Our approach will allow rapid reconstruction of unique pathway/network motifs that closely correlate with given condition, disease or phenotype ("signature networks"). Such networks could then serve as means for finding/validating drug targets and biomarkers, predicting response to a treatment and designing a new generation of diagnostic tools. In phase I, we will develop several algorithms and prototype software for automated reconstruction of such condition-specific pathways. We will test and validate developed algorithms using large set of high quality microarray data from myeloma cell lines obtained by our collaborators at Van Andel Research Institute (VARI). In phase II developed algorithms will be applied to various sets of molecular data obtained from clinical samples available at VARI (approximately 1,000 samples) and further refined for reconstruction of disease "signature networks". Commercial potential of the research will be realized through three major channels: 1) developing new analytical modules for our existing MetaCore(tm) platform; 2) generating intellectual property by analyzing data from clinical samples in collaboration with Van Andel Research Institute; 3) entering into collaborative agreements with major drug companies for the expert analysis of in-house data.